To Lure India’s Scarce AI Talent, Govt is Ready to Outpay Even the Vice President

The government’s AI push is increasingly turning into a talent war with the private sector. As Big Tech, AI startups, and global capability centres (GCCs) compete for India’s best AI engineers, data scientists, architects, and MLOps specialists, the central government is also looking to tap into the same pool and is willing to spend significantly to do so.

According to a report by ThePrint, the government is willing to pay suppliers up to ₹4.58 lakh a month for some senior AI specialists, equivalent to roughly ₹55 lakh a year. While the amount includes overheads and margins, it indicates that the government is prepared to spend to access scarce AI skills.

A person in the Ministry of Electronics and Information Technology, aware of the matter, tells AIM that the move marks a significant step toward developing AI capabilities on homegrown platforms by reducing India’s dependence on external platforms and leveraging open models. The broader ambition is to build a larger domestic AI talent pool and equip 1 crore youth with AI capabilities.

That’s why the government is bent on matching private sector salaries, and the rate is non-negotiable.

Government’s AI Rate Card

According to ThePrint, the figures are part of a Request for Empanelment reopened by the National e-Governance Division (NeGD)

An AI/Solution Architect, Data Science Lead, and AI/ML Lead can command ₹4.58 lakh a month, while an AI/ML Engineer, Data Scientist, and MLOps Lead can fetch around ₹3.2 lakh per month. Some specialised niche roles can command nearly ₹4.81 lakh a month.

This is higher than the net monthly salary of the Vice President, and just short of what the President of India earns.

The spending follows NeGD’s wider recruitment trail in 2026. The organisation has increasingly sought specialised AI capabilities—including AI/ML engineering, MLOps, AI architecture, AI product management, AI safety, and AI quality assurance.

What is Government Building?

NeGD is looking to build the infrastructure to operate AI at scale across government. The ambition is to assemble the full AI stack—from model development and infrastructure to productisation, safety, testing and governance—inside the government ecosystem.

One key objective is an in-house, multi-tenant inference server using government infrastructure, including NIC’s MeghRaj cloud, with AI models exposed through stable APIs that government applications can use. Potential applications span government workflows and citizen services—from summarising Cabinet notes, tenders, and policy documents to powering multilingual chatbots on platforms such as UMANG and DigiLocker.

The requirement also extends to voice-based interfaces for government forms, systems that extract information from certificates and scanned documents, and face-verification tools for applications such as attendance, eKYC, and digital onboarding.

Alongside AI engineers, NeGD is seeking people who can build conversational and agentic interfaces, secure LLM and RAG systems, and protect AI agents against prompt injection, jailbreaks, and data leakage.

The Digital India BHASHINI Division is similarly hiring young professionals across AI engineering, ML engineering, cybersecurity, open-source development, and Indian-language technology.

Private Sector Talent Pool and Pay

Much of the talent the government needs already sits inside India's IT companies, GCCs, and AI startups.

Nitin Mohan, AVP (Sales) at Cyfuture India, which is involved in sourcing talent for government projects, says recruitment happens through essentially the same channels used across the private sector.

“Sourcing is through different channels like Naukri.com, references, LinkedIn, etc,” he tells AIM.

However, Mohan argues that candidates are not necessarily choosing government projects over private companies because of compensation. “At the end, every client is a different client, be it private or government,” he states.

Shantanu Rooj, Founder and CEO of TeamLease EdTech, believes compensation is only one part of the equation for experienced AI professionals.

“For specialised talent, the proposition is increasingly about the nature and impact of the work, not compensation alone. Government digital projects offer professionals the opportunity to work on platforms and use cases that operate at population scale, potentially influencing how public services are delivered to millions of citizens,” he says.

He points to NeGD’s requirements across AI/ML engineering, data science, MLOps, AI architecture, and AI-enabled applications as evidence that government technology projects are becoming substantially more sophisticated.

“For experienced professionals, the attraction can therefore be a combination of mission, scale, visibility of impact, and exposure to complex public-sector problems,” Rooj says. “The government's opportunity is to make these roles technically challenging and professionally rewarding enough that specialised talent sees public digital infrastructure as a meaningful career opportunity, rather than simply comparing it with private-sector compensation.”

But there is a structural constraint. The ₹4.58 lakh figure is a supplier rate, not necessarily an employee salary. The actual compensation available to an AI specialist will depend on the staffing vendor, its margins, and the employment arrangement.

AI Talent Problem Runs Deeper

However, the government faces the same AI talent shortfall as the private sector. According to a joint report by Nasscom and McKinsey & Co, India needs a talent pool of 1 million AI-skilled professionals, against the current talent pool of roughly 500,000–650,000 professionals.

“The challenge is less about whether India has AI talent and more about whether enough of it is specialised, industry-ready, and available for the problems the government needs to solve,” Rooj says.

NeGD’s own requirements illustrate the problem. Senior AI/ML and architecture roles require several years of industry experience, putting government projects in direct competition with private employers for a relatively small pool of experienced professionals.

“The sustainable answer is therefore twofold: attract experienced specialists while simultaneously expanding the pipeline through universities, work-linked learning, apprenticeships, and industry exposure,” he adds.

There is another important shift in the government's approach. According to ThePrint, the latest empanelment exercise lowers the minimum turnover requirement from ₹50 crore to ₹25 crore, while the employee requirement has been reduced from 200 to 100. MSMEs and startups are exempt from both requirements.

That could widen the pool of suppliers through which the government accesses AI talent, but also increase competition for India's AI workforce.

The government now hopes that a combination of high-value project rates, public-sector scale, mission, and access to some of the country's most consequential technology problems will be enough to pull experienced AI professionals away from AI startups.